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The Serial Peripheral Interface (SPI) is popular as a simple, low-cost interface between multiple devices such as microcontrollers, sensors, and actuators.
By using a FRAM-based microcontroller instead of flash-based, designers can reduce the power required to update firmware over a LoRaWAN wireless network.
A modular system design provides a compact solution to emerging requirements for next generation PLCs.
Developers can implement the basic analog interfaces required in many wearable and IoT designs using only an MCU and a few passive components.
Developers can rapidly deploy sensor hardware and software needed to build sophisticated solutions for industrial predictive maintenance.
Designers can add an external secure EEPROM to a microcontroller that provides an efficient way to protect sensitive data from hackers.
Using a security IC and a software library, developers can employ a more efficient approach to mutual authentication required for IoT security.
Developers should consider these low-power processor and board solutions to implement efficient machine learning on IoT devices at the network edge.
Developers can use low-cost boards and specialized LEDs to build a complete greenhouse control system.
Second generation GNSS modules offer faster satellite acquisition and better positional accuracy while becoming easier to design in.
Use highly integrated modular gate drives to save BLDC motor control circuit space and make it easier to control MOSFET switching for optimum performance.
Integrated time of flight (ToF) sensors provide a simple, fast, and inexpensive way to measure distance and to recognize simple gestures in embedded systems.
The Arduino MKR Vidor 4000 provides a simple and inexpensive way to make use of an FPGA’s real time abilities in embedded system designs.
Securing embedded systems using the Armv8-M architecture and TrustZone.
Using a family of 32-bit MCUs to build invisible intelligence into wearables and IoT devices while optimizing for low power.
Developers can use secure MCUs and authentication ICs to meet users' expectations for privacy and protection in smart products.
Developers can implement efficient KWS on MCUs using DS-CNNs from hardware optimized neural network library for resource-constrained designs.
Advanced MCUs and PMICs provide the foundation needed to meet user expectations for next generation smart products.
Developers can add voice-activated features to resource-constrained designs using a low-power FPGA running a BNN, a highly efficient machine learning algorithm.
Implement real-time clock/calendar (RTCC) functions in embedded systems with minimal design time, component count, and power consumption.
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